Staff AV Behavior Safety Engineering Lead

Description
At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features.
Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale.
The Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department is part of GM's Global Product Safety, System, and Certification (GPSSC) organization. Our mission is to help GM deliver trusted automated-driving products. As the central authority for automated driving system (ADS) safety, SAFE-ADS brings together experts from across the company to develop and maintain a comprehensive safety case including safety performance indicators for GM's automated-driving technologies.
GM's vision is zero crashes, zero emissions, and zero congestion-and autonomous vehicle safety is essential to achieving that vision.
As Staff AV Behavior and AI Safety Engineer , you will lead the strategy and support execution for how GM defines, measures, and validates the safety of SAE Level 3 - 4 Automated Driving Systems powered by machine-learned models. You will report into the AV Safety Strategy and Assurance organization and directly influence launch decisions for GM's next generation of automated driving products.
If you are passionate about safety, have deep experience in autonomous vehicle development and validation, and are a proven technical leader in AI/ML-driven systems, this role is an opportunity to shape how millions of people experience safe automated driving.
The Role
The AV Safety Strategy and Assurance team is seeking a hands-on Principal engineer with extensive experience in the end-to-end development lifecycle of autonomous vehicle behaviors, from ADS Architecture, ODD and behavior definition through simulation, closed-course, and public-road validation.
If you're excited to lead in autonomous driving safety, we'd love to hear from you!
Why This Role Is Unique:

• Impact at Scale: Your work will directly influence how GM brings safe automated driving systems to millions of customers.

• End-to-End Ownership: You will own the strategy, framework, and evidence assessment for AV behavior and AI safety.

• Cross-Functional Reach: You will collaborate across AI, software, validation, simulation, metrics operations and vehicle program teams, shaping the direction of GM's automated driving roadmap.

What You'll Do (Responsibilities):

• Own AI and AV behavior safety strategy for next generation ADS architectures

• Design and implement AI Safety strategies for cutting-edge AI Models like Imitation Learning and Reinforcement learning.

• Own the behavior-focused portion of the ADS Safety Case, including key claims, sufficiency criteria, and recommended evidence for AV behavior safety performance.

• Collaborate with Software Validation, Embodied AI, Simulation, and Safety Metrics teams to define the end-to-end AV behavior validation and AI safety methodology for AI-driven systems.

• Collaborate on evaluation metrics, human benchmarks, and safety launch targets for AV behaviors, AI Safety, and overall system performance.

• Innovate and co-develop safety performance indicators (SPIs) for AV behaviors.

• Innovate and co-develop metrics for all stages of ML model development lifecycle

• Reference and interpret standards such as ISO/PAS 8800 (AI Safety), ISO 21448 (SOTIF), ISO 5083, and AVSC best practices to define GM's strategy for safe autonomous system development, validation and deployment

• Assess AV performance across safety and reliability dimensions using simulation, closed-course, and public-road data and provide clear, prioritized feedback to engineering teams

• Define and run an assurance process to verify the sufficiency criteria and safety targets to support launch readiness

Your Skills & Abilities (Required Qualifications):

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field

• 7+ years of experience in machine learning, engineering, data science, or a related field

• 7+ years in autonomous vehicle or robotics development or related field

• Demonstrated experience working on production-intent AV programs

• Track record providing technical safety leadership in AV development (e.g., defining safety strategies, risk assessments, validation methodologies, safety case contributions).

• Deep understanding of AV behavior development: defining ODDs, behaviors, and evaluation criteria; analyzing simulation, closed-course, and public-road test data; and generating prioritized, actionable recommendations for developers.

• Experience with ML model evaluation methodologies and ML model development Lifecyle

• Experience applying AV safety standards and best practices, such as ISO/PAS 8800, ISO 5083, ISO 21448 (SOTIF), and AVSC practices

• Excellent communication and storytelling skills, including the ability to explain complex technical tradeoffs to executives and non-technical stakeholders.

• Proven ability to influence cross-functional teams (Software, AI/ML, Systems Engineering, Product, Program Management, Operations) without direct authority.

• Strong problem-solving mindset, comfort with ambiguity, and a proactive attitude toward learning and continuous improvement.

What Will Give You A Competitive Edge (Preferred qualifications):

• Masters Degree in Computer Science, Engineering, Mathematics or related field

• Machine Learning & AI: Large Language Models (LLMs), Generative AI, Deep learning, Imitation Learning, Reinforcement Learning,

• Cloud & Big Data Platforms: Google Cloud Platform (BigQuery, Dataflow)

• Deployment & MLOps: MLflow, Model Monitoring & Versioning, GitHub, Jira

Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate. • The salary range for this role is $185,100 and $284,100. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits: • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
Company vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, though which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
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This role is categorized as remote. This means the selected candidate may be based anywhere in the country of work and is not expected to report to a GM worksite unless directed by their manager.
The selected candidate will be required to travel <25% for this role.
About GM
Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
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